Distributed Decision Making and Situation Awareness in Sensor Networks

在这个项目中，我们从控制理论的角度研究了传感器网络的决策和态势感知。在态势感知方面，我们提出了一种新颖的视觉传感器网络协同估计问题，并在此基础上扩展了前人的研究成果，提出了一种新的解决方案。我们还提出了一种独特的基于初始调度的机器人传感器网络分布式任务切换算法。然后，我们还提出了一种融合随机化技术和博弈论的决策学习算法。所有这些结果都已经被国内期刊接受并在国际会议上发表。此外，他们的复杂版本被提交给国际期刊。我们还搭建了传感器网络系统的试验台进行验证，结果得到了国内外研究者的高度评价。

In this project, we have investigated decision making and situation awareness for sensor networks from a viewpoint of control theory. In terms of situation awareness, we have formulated an original cooperative estimation problem for visual sensor networks and presented a novel solution to the problem by extending results of our previous works. We also have presented a unique distributed task-switching algorithm for robotic sensor networks according to the initial schedule. Then, we also have presented a novel learning algorithm for decision-making by fusing randomized techniques and game theory. All of these results have been already accepted for publication for domestic journals and for presentation at international conferences. In addition, their sophisticated versions are submitted to international journals. We have also built a testbed of a sensor network system for verification and the results are highly appreciated by the domestic and foreign researchers.